UGA researchers find social media patterns that might help businesses

Saturday

May 24, 2014 at 2:59 PM

Allie Jackson

It turns out the way people interact on social media is similar to that of real life - in communities.

Researchers at the University of Georgia narrowed it down further and after months of research, determined there are six distinct categories. It's research they believe will help business owners better understand clientele.

HOW IT WAS DONE

"When people interact on social media such as Twitter it creates structures - patterns of social interaction. This falls under different categories, but we never had the ability to see the interactions and find the different types of connections that people make," said UGA Grady College assistant professor Itai Himelboim, who spearheaded the project. "And that's what we did here. We went into a depository of hundreds of thousands of Twitter conversations ... from politics to health to news to various hobbies."

Himelboim worked with the Pew Research Center and Social Media Foundation to identify the recurring message patterns utilizing a free and open social media network analysis tool created by the Social Media Research Foundation called NodeXL. He compared it to a zoologist noticing distinct characteristics in one type of animal.

"They may see one animal and then another with very similar features and say, 'Hey, that's probably one type of animal,'" he said. "Yes, there are obviously differences amongst them, such as breeds, but they are one type."

WHAT IT LOOKS LIKE

Himelboim said the team was able to identify each type of structure and explain their differences by looking at information flow amongst users and information sources. The six structures include polarized crowds, tight crowds, brand clusters, community clusters, broadcast networks and support networks.

While polarized crowds are divided, tight crowds are more unified. An example of a polarized crowd would be a political group. While both groups may be about politics, each is mainly tweeting amongst the political party they favor. Tight crowds form amongst like-minded people, so typically include conversations about hobbies or professional topics.

Similarly, brand clusters are fragmented while community clusters branch off in smaller clusters and chat back and forth. Celebrities are discussed in brand clusters while global news is often discussed in community clusters.

Broadcast networks are often started by news companies pushing out breaking news, while a support network is customers reaching out for products or services.

HOW IT CAN HELP A BUSINESS

Himelboim believes the information will help companies discover the best way to market and communicate with clientele.

"If businesses can find what category they are in, whether a community cluster versus a brand, this will allow them a starting point ... if they are a brand, but want to be a community," he said. "And they will know the group of people they are talking to, but it also gives them the information about groups who may not be talking to them, but are talking about them and that's very useful to find out who they are, what they say and, more importantly, who connected them to you."

THE SCIENCE BEHIND IT

Pew Research Center's Internet & American Life Project Director Lee Rainie also helped on the project, which he said made him feel like a child with a new toy.

Rainie said the project was a new way of looking at the world in terms of social media. He compared the project to that of an archeologist studying rocks.

"We didn't start out with any theories. We basically observed. And after looking at tens of thousands of maps, we really started seeing the patterns developing," said Rainie. "We were literally placing social media conversations under a microscope and discovering that there were different structures."

While the team discovered six main structures, Rainie said there may be more to it than that.

"I'm not about to argue that this is everything. The exciting thing about social sciences is you find stuff and then other people join in and maybe thanks to these new mapping tools and clever people, we will five or seven years from now have a richer picture," he said. "It's a brand new way to take a snapshot and see what social interactions look like. And everybody seems to be linked to each other. And it's just sort of gorgeous because that's exactly what a community looks like."

WHY USE IT?:

Businesses get a virtual picture of the relationship it has with the community.

"It can help a business identify the communities it wants to be a part of. Identify key communities and the key users that play a meaningful role," said Himelboim. "You can identify those people or organizations ... identify the conversations you want to be a part of and then start building relationships with these key users by following them, retweeting them, mentioning them, communicating with them. Find out what key words or hashtags they are using and start using them yourself ... and start applying the same social media strategies."

A summary of the research findings is available at www.pewinternet.org/2014/02/20/mapping-twitter-topic-networks-from-polarized-crowds-to-community-clusters/. Using the NodeXL program is free and open to the public.